opencv 使用XML和YAML格式来输入输出文件

源码

链接 link

#include <opencv2/core.hpp>
#include <iostream>
#include <string>

using namespace cv;
using namespace std;

// 帮助信息函数
static void help(char** av)
{
    cout << endl
         << av[0] << " shows the usage of the OpenCV serialization functionality." << endl
         << "usage: " << endl
         << av[0] << " outputfile.yml.gz" << endl
         << "The output file may be either XML (xml) or YAML (yml/yaml). You can even compress it by "
         << "specifying this in its extension like xml.gz yaml.gz etc... " << endl
         << "With FileStorage you can serialize objects in OpenCV by using the << and >> operators" << endl
         << "For example: - create a class and have it serialized" << endl
         << " - use it to read and write matrices." << endl;
}

// 自定义数据结构 MyData
// 主要提供序列化和反序列化相关的读写功能
class MyData
{
public:
    MyData() : A(0), X(0), id() {}
    explicit MyData(int) : A(97), X(CV_PI), id("mydata1234") {}
    
    void write(FileStorage& fs) const
    {
        fs << "{" << "A" << A << "X" << X << "id" << id << "}";
    }

    void read(const FileNode& node)
    {
        A = (int)node["A"];
        X = (double)node["X"];
        id = (string)node["id"];
    }

public:
    int A;
    double X;
    string id;
};

// 序列化和反序列化的辅助函数
static void write(FileStorage& fs, const std::string&, const MyData& x)
{
    x.write(fs);
}

static void read(const FileNode& node, MyData& x, const MyData& default_value = MyData())
{
    if (node.empty())
        x = default_value;
    else
        x.read(node);
}

// 重载输出运算符
static ostream& operator<<(ostream& out, const MyData& m)
{
    out << "{ id = " << m.id << ", ";
    out << "X = " << m.X << ", ";
    out << "A = " << m.A << "}";
    return out;
}

// 主函数
int main(int ac, char** av)
{
    if (ac != 2)
    {
        help(av);
        return 1;
    }

    string filename = av[1];
    { // 写操作
        Mat R = Mat_<uchar>::eye(3, 3),
            T = Mat_<double>::zeros(3, 1);
        MyData m(1);

        FileStorage fs(filename, FileStorage::WRITE);

        fs << "iterationNr" << 100;
        fs << "strings" << "["; 
        fs << "image1.jpg" << "Awesomeness" << "../data/baboon.jpg";
        fs << "]"; 

        fs << "Mapping";
        fs << "{" << "One" << 1;
        fs << "Two" << 2 << "}";

        fs << "R" << R; 
        fs << "T" << T;

        fs << "MyData" << m;

        fs.release(); 
        cout << "Write Done." << endl;
    }

    { // 读操作
        cout << endl << "Reading: " << endl;
        FileStorage fs;
        fs.open(filename, FileStorage::READ);

        if (!fs.isOpened())
        {
            cerr << "Failed to open " << filename << endl;
            help(av);
            return 1;
        }

        int itNr;
        itNr = (int) fs["iterationNr"];
        cout << itNr << endl;

        FileNode n = fs["strings"];
        if (n.type() != FileNode::SEQ)
        {
            cerr << "strings is not a sequence! FAIL" << endl;
            return 1;
        }

        FileNodeIterator it = n.begin(), it_end = n.end();
        for (; it != it_end; ++it)
            cout << (string)*it << endl;

        n = fs["Mapping"];
        cout << "Two " << (int)(n["Two"]) << "; ";
        cout << "One " << (int)(n["One"]) << endl << endl;

        MyData m;
        Mat R, T;

        fs["R"] >> R;
        fs["T"] >> T;
        fs["MyData"] >> m;

        cout << "R = " << R << endl;
        cout << "T = " << T << endl << endl;
        cout << "MyData = " << endl << m << endl << endl;

        cout << "Attempt to read NonExisting (should initialize the data structure with its default).";
        fs["NonExisting"] >> m;
        cout << endl << "NonExisting = " << endl << m << endl;
    }

    cout << endl
         << "Tip: Open up " << filename << " with a text editor to see the serialized data." << endl;

    return 0;
}

解析

1. XML/YAML文件的开关。
   在Opencv中XML和YAML的数据结构是cv::FileStorage。

 FileStorage fs(filename, FileStorage::WRITE);
 // or:
 // FileStorage fs;
 // fs.open(filename, FileStorage::WRITE);

该文件会在cv::FileStorage对象被销毁时自动关闭，但是你还是需要使用释放函数来额外声明一下。

fs.release(); // explicit close

2. 文本和数字的输入输出。
   在c++中，数据结构使用STL库中的<<输出操作符，如下所示。

 fs << "iterationNr" << 100;

读入是一个简单的寻址(通过[]操作符)和强制类型转换操作，或者通过>>操作符进行读操作。

 int itNr;
 //fs["iterationNr"] >> itNr;
 itNr = (int) fs["iterationNr"];

3. Opencv数据结构的输入输出

 Mat R = Mat_<uchar>::eye(3, 3),
 T = Mat_<double>::zeros(3, 1);
 fs << "R" << R; // cv::Mat
 fs << "T" << T;
 fs["R"] >> R; // Read cv::Mat
 fs["T"] >> T;

4. vector和相关map的输入输出

5. 读写数据结构
   举一个数据结构的例子

class MyData
{
public:
 MyData() : A(0), X(0), id() {}
public: // Data Members
 int A;
 double X;
 string id;
};

在c++中，可以通过OpenCV I/O XML/YAML接口(就像OpenCV数据结构的情况一样)通过在类内外添加读和写函数来序列化它。

 void write(FileStorage& fs) const //Write serialization for this class
 {
 	fs << "{" << "A" << A << "X" << X << "id" << id << "}";
 }
 void read(const FileNode& node) //Read serialization for this class
 {
 	A = (int)node["A"];
 	X = (double)node["X"];
 	id = (string)node["id"];
 }

在C++中，你还需要添加在该类之外的函数定义：

static void write(FileStorage& fs, const std::string&, const MyData& x)
{
 	x.write(fs);
}
static void read(const FileNode& node, MyData& x, const MyData& default_value = MyData()){
 	if(node.empty())
 		x = default_value;
 	else
 		x.read(node);
}

在这里，您可以观察到，在read部分中，我们定义了如果用户试图读取不存在的节点会发生什么。在这种情况下，我们只返回默认的初始化值，然而，更详细的解决方案是返回例如对象ID的- 1值。

添加了这四个函数后，使用>>操作符进行写操作，使用<<操作符进行读操作。

 MyData m(1);
 fs << "MyData" << m; // your own data structures
 fs["MyData"] >> m; // Read your own structure_

或：

 cout << "Attempt to read NonExisting (should initialize the data structure with its default).";
 fs["NonExisting"] >> m;
 cout << endl << "NonExisting = " << endl << m << endl;

结果

Write Done.
 
Reading:
100image1.jpg
Awesomeness
baboon.jpg
Two 2; One 1
 
 
R = [1, 0, 0;
 0, 1, 0;
 0, 0, 1]
T = [0; 0; 0]
 
MyData =
{ id = mydata1234, X = 3.14159, A = 97}
 
Attempt to read NonExisting (should initialize the data structure with its default).
NonExisting =
{ id = , X = 0, A = 0}
 
Tip: Open up output.xml with a text editor to see the serialized data.

输出

XML

<?xml version="1.0"?>
<opencv_storage>
<iterationNr>100</iterationNr>
<strings>
 image1.jpg Awesomeness baboon.jpg</strings>
<Mapping>
 <One>1</One>
 <Two>2</Two></Mapping>
<R type_id="opencv-matrix">
 <rows>3</rows>
 <cols>3</cols>
 <dt>u</dt>
 <data>
 1 0 0 0 1 0 0 0 1</data></R>
<T type_id="opencv-matrix">
 <rows>3</rows>
 <cols>1</cols>
 <dt>d</dt>
 <data>
 0. 0. 0.</data></T>
<MyData>
 <A>97</A>
 <X>3.1415926535897931e+000</X>
 <id>mydata1234</id></MyData>
</opencv_storage>

YAML

%YAML:1.0
iterationNr: 100
strings:
 - "image1.jpg"
 - Awesomeness
 - "baboon.jpg"
Mapping:
 One: 1
 Two: 2
R: !!opencv-matrix
 rows: 3
 cols: 3
 dt: u
 data: [ 1, 0, 0, 0, 1, 0, 0, 0, 1 ]
T: !!opencv-matrix
 rows: 3
 cols: 1
 dt: d
 data: [ 0., 0., 0. ]
MyData:
 A: 97
 X: 3.1415926535897931e+000
 id: mydata1234

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